Ischemia is a common ailment that affects millions of people. Ischemia is a restriction in the blood supply to biological tissues causing a shortage of oxygen and glucose needed for cellular metabolism. As a result, damage or dysfunction may result in the tissues, and a local anemia may develop in parts of the body resulting from congestion. A patient suffering from ischemia may experience irreversible damage to bodily tissues in as little as 20 minutes. A more severe manifestation of disease may lead to tissue necrosis and/or gangrene. Significant strides have been made in the measurement of ischemia including using specialized imaging techniques (e.g., Contrast-Enhanced Magnetic Resonance Imaging (CEMRI), Fludeoxyglucose Positiron Emission Tomography (FDG-PET), stress echo/MRI, multidetector CT, and/or dual energy CT). However, these imaging techniques may incur a significant financial expense and may also expose a patient to additional radiation. Furthermore, the equipment required to perform the specialized imaging techniques may not be available at some facilities. Since viability is the degree to which a vessel, tissue, or organ is functional, an ischemia may result in reduced viability of the underlying vessel, tissue, or organ. Thus, a desire exists to use available patient information to estimate a viability characteristic in a target tissue, where the estimated viability data may be obtained by machine learning from a patient-specific vascular and/or anatomical model, and by using any other additional data that may be available. Since the vascular and/or anatomical model may be derived from several imaging techniques, the embodiments of the present disclosure may enable use of a single scan to assess both tissue anatomy and tissue viability.
The foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.